Class "GBH"

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Description

Class to facilitate performing the Group
Benjamini-Hochberg procedure and interpreting its output.

Slots

p.vals:

Object of class "data.frame". Each
row correpsonds to an individual hypothesis. The first column
stores the p-values before GBH adjustment, while the second
gives the GBH adjusted p-values. The hypotheses are sorted
in order of significance according to these GBH adjusted
p-values. The group column gives the group membership
of each hypothesis, and adj.significnace codes the
significance of each hypothesis, according to the GBH adjusted
p-values.

pi0:

Object of class "numeric". The proportion
of null hypotheses within each group. This is either known
a priori or estimated adaptively from the unadjusted p-values.

adaptive:

Object of class "logical". An
indicator of whether the proportion pi0 was estimated
adaptively from the data or known a priori.

alpha:

Object of class "numeric". The level
at which the FDR is controlled, during the GBH procedure.

Methods

plot

signature(x = "GBH", y = "ANY"):
...

Plots the p-values of the hypothesis, sorted according to
GBH adjusted significance, shape coded according to group
membership, and color coded according to pre and post
GBH p-value adjustment.

show

signature(object = "GBH"): ...

Prints the
entire table of adjusted p-values and their associated FDR adjusted
significance levels, together with the estimated proportions
of null hypotheses, within each group.

summary

signature(object = "GBH"): ...

Prints
the most significant hypothesis, after adjusting for multiple
testing via GBH. Also supplies the estimated proportion of null
hypothesis within each group and a table of counts of
adjusted significance across groups.

See Also

Adaptive.GBHOracle.GBH

Examples

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## These are the unadjusted p-values corresponding to## the outcome of some multiple testing experiment. The## first 500 hypotheses are null and the last 1500 are## true alternatives.
unadjp <-c(runif(500,0,0.01),runif(1500,0,1))names(unadjp)<-paste("Hyp: ",1:2000)## These are the unadjusted p-values corresponding to## the outcome of some multiple testing experiment. The## first 500 hypotheses are null and the last 1500 are## true alternatives.
unadjp <-c(runif(500,0,0.01),runif(1500,0,1))names(unadjp)<-paste("Hyp: ",1:2000)## Here there are two groups total we have randomly## assigned hypotheses to these two groups.
group.index <-c(sample(1:2,2000,replace=TRUE))# Perform the GBH adjustment.
result <-Adaptive.GBH(unadjp, group.index, method ="storey")# A summary of the GBH adjustmentsummary(result)